-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\knm4642\Dropbox\Nha Meo Heo Beo\_JMP\WORKING FOLDER\Table A13_Effect by gender and gender norms.log
  log type:  text
 opened on:  18 Feb 2026, 23:53:29

.         
. //PREPARE DATA
. use "Baseline CEO firm year sample.dta", clear

. * set globals
. global firm = "firmage firmage2"

. global ceo = "gender age age2 yrinco i.education"

. global sample = "year < 2012 & !nonUS"

. global cluster = "mainethcode"

. 
. 
. //PREPARE TABLE
. * PANEL A: CEO's trust effect by CEO's gender and gender norms
. eststo clear

. eststo col1: /// by CEO's gender
>         reghdfe ash_f1allpat c.trust_sd##i.gender ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)
note: gender omitted because of collinearity

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  11,     37) =      43.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                                (Std. err. adjusted for 38 clusters in mainethcode)
-----------------------------------------------------------------------------------
                  |               Robust
     ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         trust_sd |   .0613986   .0182295     3.37   0.002     .0244621    .0983352
         2.gender |   -.096706   .4869765    -0.20   0.844    -1.083414    .8900022
                  |
gender#c.trust_sd |
               2  |   .0166533   .0983953     0.17   0.867    -.1827146    .2160211
                  |
          firmage |  -.0109599   .0018914    -5.79   0.000    -.0147923   -.0071276
         firmage2 |   .0001159   .0000492     2.36   0.024     .0000162    .0002156
           gender |          0  (omitted)
              age |  -.0012257   .0102786    -0.12   0.906    -.0220521    .0196008
             age2 |  -6.01e-06   .0000844    -0.07   0.944    -.0001771    .0001651
           yrinco |   .0040681   .0005472     7.43   0.000     .0029593    .0051768
                  |
        education |
               2  |   .0427659   .0484186     0.88   0.383    -.0553394    .1408712
               3  |   .0593235   .0334553     1.77   0.084    -.0084634    .1271104
               4  |   .0838844    .041538     2.02   0.051    -.0002795    .1680483
                  |
            _cons |    .807319   .2761632     2.92   0.006     .2477592    1.366879
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col1, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col2: /// CEO's gender norms control
>         reghdfe ash_f1allpat trust_sd LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  11,     37) =      22.56
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0605448   .0160254     3.78   0.001     .0280742    .0930154
   LFPR_sd_c |   .0072178   .0224672     0.32   0.750     -.038305    .0527407
     firmage |  -.0109163   .0019721    -5.54   0.000    -.0149122   -.0069204
    firmage2 |   .0001157   .0000493     2.35   0.024     .0000158    .0002157
      gender |   -.012191   .0333015    -0.37   0.716    -.0796664    .0552843
         age |  -.0012349   .0103385    -0.12   0.906    -.0221826    .0197129
        age2 |  -6.03e-06   .0000848    -0.07   0.944    -.0001779    .0001658
      yrinco |   .0040747   .0005526     7.37   0.000     .0029551    .0051943
             |
   education |
          2  |   .0422494   .0483719     0.87   0.388    -.0557614    .1402602
          3  |   .0586968   .0335161     1.75   0.088    -.0092133    .1266069
          4  |   .0836565    .041186     2.03   0.049     .0002058    .1671073
             |
       _cons |   .8244667   .3044068     2.71   0.010       .20768    1.441254
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col2, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col3: /// by CEO's gender norms
>         reghdfe ash_f1allpat c.trust_sd##c.LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      19.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                                     (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------------
                       |               Robust
          ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              trust_sd |    .058797   .0157618     3.73   0.001     .0268606    .0907334
             LFPR_sd_c |   .1393154   .1306616     1.07   0.293    -.1254301    .4040609
                       |
c.trust_sd#c.LFPR_sd_c |  -.0281492   .0280072    -1.01   0.321    -.0848972    .0285989
                       |
               firmage |   -.011001   .0019926    -5.52   0.000    -.0150383   -.0069637
              firmage2 |   .0001162   .0000493     2.36   0.024     .0000163     .000216
                gender |  -.0126231   .0334499    -0.38   0.708    -.0803989    .0551528
                   age |  -.0011696   .0103531    -0.11   0.911     -.022147    .0198078
                  age2 |  -6.91e-06    .000085    -0.08   0.936     -.000179    .0001652
                yrinco |   .0040585   .0005568     7.29   0.000     .0029303    .0051867
                       |
             education |
                    2  |   .0415027    .048316     0.86   0.396    -.0563948    .1394003
                    3  |   .0580528   .0334353     1.74   0.091    -.0096936    .1257992
                    4  |    .082948   .0412916     2.01   0.052    -.0007168    .1666128
                       |
                 _cons |     .83525   .3026952     2.76   0.009     .2219313    1.448569
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col3, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col4: /// citation-weighted, by CEO's gender
>         reghdfe ash_f1allpat_citff c.trust_sd##i.gender ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)
note: gender omitted because of collinearity

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  11,     37) =      45.50
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8362
                                                  Adj R-squared   =     0.8132
                                                  Within R-sq.    =     0.0014
Number of clusters (mainethcode) =         38     Root MSE        =     1.1065

                                (Std. err. adjusted for 38 clusters in mainethcode)
-----------------------------------------------------------------------------------
                  |               Robust
ash_f1allpat_c~ff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
------------------+----------------------------------------------------------------
         trust_sd |   .0960481   .0320798     2.99   0.005     .0310483     .161048
         2.gender |  -.4317166     1.3831    -0.31   0.757    -3.234143    2.370709
                  |
gender#c.trust_sd |
               2  |   .0961253   .2796089     0.34   0.733    -.4704161    .6626668
                  |
          firmage |  -.0367108   .0061642    -5.96   0.000    -.0492007   -.0242209
         firmage2 |   .0001587   .0000869     1.83   0.076    -.0000173    .0003348
           gender |          0  (omitted)
              age |  -.0194596   .0213655    -0.91   0.368    -.0627502    .0238309
             age2 |   .0001714    .000181     0.95   0.350    -.0001954    .0005381
           yrinco |   .0054808   .0011852     4.62   0.000     .0030793    .0078822
                  |
        education |
               2  |    .008417   .1507753     0.06   0.956    -.2970828    .3139167
               3  |   .0279011   .1243465     0.22   0.824     -.224049    .2798511
               4  |   .0688199   .1421057     0.48   0.631    -.2191137    .3567535
                  |
            _cons |   2.280971   .5323591     4.28   0.000     1.202309    3.359633
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col4, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col5: /// citation-weighted, CEO's gender norms control
>         reghdfe ash_f1allpat_citff trust_sd LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  11,     37) =      43.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8362
                                                  Adj R-squared   =     0.8132
                                                  Within R-sq.    =     0.0015
Number of clusters (mainethcode) =         38     Root MSE        =     1.1065

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1all~ff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0867995   .0281201     3.09   0.004     .0298226    .1437763
   LFPR_sd_c |   .0649166   .0401913     1.62   0.115    -.0165187    .1463519
     firmage |  -.0362906   .0063121    -5.75   0.000    -.0490801   -.0235012
    firmage2 |   .0001568   .0000863     1.82   0.077    -.0000179    .0003316
      gender |    .055098   .0655622     0.84   0.406    -.0777437    .1879397
         age |  -.0195652   .0216182    -0.91   0.371     -.063368    .0242375
        age2 |   .0001714   .0001834     0.93   0.356    -.0002001    .0005429
      yrinco |    .005547   .0011738     4.73   0.000     .0031687    .0079254
             |
   education |
          2  |   .0041853   .1490233     0.03   0.978    -.2977647    .3061352
          3  |   .0226437   .1225518     0.18   0.854    -.2256699    .2709573
          4  |   .0672203   .1408353     0.48   0.636    -.2181392    .3525798
             |
       _cons |   2.278056   .5656573     4.03   0.000     1.131925    3.424186
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col5, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col6: /// citation-weighted, by CEO's gender norms 
>         reghdfe ash_f1allpat_citff c.trust_sd##c.LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      40.25
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8362
                                                  Adj R-squared   =     0.8132
                                                  Within R-sq.    =     0.0016
Number of clusters (mainethcode) =         38     Root MSE        =     1.1065

                                     (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------------
                       |               Robust
    ash_f1allpat_citff | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              trust_sd |   .0837813   .0264453     3.17   0.003     .0301981    .1373645
             LFPR_sd_c |    .293026    .244429     1.20   0.238    -.2022343    .7882863
                       |
c.trust_sd#c.LFPR_sd_c |  -.0486087   .0491357    -0.99   0.329     -.148167    .0509496
                       |
               firmage |  -.0364369   .0063504    -5.74   0.000    -.0493041   -.0235697
              firmage2 |   .0001576   .0000863     1.83   0.076    -.0000172    .0003324
                gender |    .054352   .0659357     0.82   0.415    -.0792463    .1879503
                   age |  -.0194524   .0216606    -0.90   0.375     -.063341    .0244361
                  age2 |   .0001699   .0001837     0.92   0.361    -.0002023    .0005421
                yrinco |   .0055191    .001169     4.72   0.000     .0031506    .0078877
                       |
             education |
                    2  |   .0028959   .1490923     0.02   0.985    -.2991937    .3049855
                    3  |   .0215317   .1226962     0.18   0.862    -.2270743    .2701377
                    4  |   .0659967   .1411919     0.47   0.643    -.2200852    .3520787
                       |
                 _cons |   2.296676   .5629452     4.08   0.000     1.156041    3.437312
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col6, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. 
. global coeflist = "trust_sd 2.gender#c.trust_sd LFPR_sd_c c.trust_sd#c.LFPR_sd_c"

. esttab /*using "Table A13_Effect by gender and gender norms_Panel A.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         nomtitle collabels(none) label varwidth(28) modelwidth(12) ///
>         mgroups("arsinh(Future patent applications)", pattern(1 0 0 0 0 0) ///
>                 prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(${coeflist}) order(${coeflist}) ///
>         coeflab(trust_sd "CEO's trust" ///
>                         2.gender#c.trust_sd "Trust $\times$ Female CEO" ///
>                         LFPR_sd_c "F/M LFP ratio (z-score)" ///
>                         c.trust_sd#c.LFPR_sd_c "Trust $\times$ F/M LFP ratio") ///
>         stats(qualweight FE controls N nofirms, fmt(%9.0fc %9.0fc) ///
>                 lab("Quality weight" "Firm \& Year FEs" "Baseline controls" "Observations" "Firms"))

----------------------------------------------------------------------------------------------------------------------------
                             \multicolumn{6}{c}{arsinh(Future patent applications)}                                         
                                      (1)             (2)             (3)             (4)             (5)             (6)   
----------------------------------------------------------------------------------------------------------------------------
CEO's trust                         0.061***        0.061***        0.059***        0.096***        0.087***        0.084***
                                  (0.018)         (0.016)         (0.016)         (0.032)         (0.028)         (0.026)   
Trust $\times$ Female CEO           0.017                                           0.096                                   
                                  (0.098)                                         (0.280)                                   
F/M LFP ratio (z-score)                             0.007           0.139                           0.065           0.293   
                                                  (0.022)         (0.131)                         (0.040)         (0.244)   
Trust $\times$ F/M LFP ratio                                       -0.028                                          -0.049   
                                                                  (0.028)                                         (0.049)   
----------------------------------------------------------------------------------------------------------------------------
Quality weight                       None            None            None       Fwd cites       Fwd cites       Fwd cites   
Firm \& Year FEs                        X               X               X               X               X               X   
Baseline controls                       X               X               X               X               X               X   
Observations                       29,384          29,384          29,384          29,384          29,384          29,384   
Firms                               3,598           3,598           3,598           3,598           3,598           3,598   
----------------------------------------------------------------------------------------------------------------------------

. 
. 
. * PANEL B: CEO's trust effect by inventors' gender and CEO's gender norms
. eststo clear

. eststo col1: /// patents by female inventors
>         reghdfe ash_f1allpat_f trust_sd ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      18.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8922
                                                  Adj R-squared   =     0.8770
                                                  Within R-sq.    =     0.0019
Number of clusters (mainethcode) =         38     Root MSE        =     0.3140

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1al~t_f | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0200251   .0071267     2.81   0.008     .0055849    .0344652
     firmage |   -.010275   .0050139    -2.05   0.048    -.0204342   -.0001158
    firmage2 |   .0000392   .0000339     1.16   0.255    -.0000295    .0001079
      gender |  -.0070254   .0206057    -0.34   0.735    -.0487764    .0347256
         age |   .0010125   .0028089     0.36   0.721    -.0046787    .0067038
        age2 |  -.0000256   .0000238    -1.08   0.289    -.0000739    .0000226
      yrinco |    .002706   .0004711     5.74   0.000     .0017516    .0036605
             |
   education |
          2  |   .0064926   .0164777     0.39   0.696    -.0268944    .0398797
          3  |   .0208925    .016839     1.24   0.223    -.0132265    .0550115
          4  |   .0213703   .0152566     1.40   0.170    -.0095426    .0522832
             |
       _cons |   .3979478   .1429521     2.78   0.008     .1082992    .6875963
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 cap drop sample

.                 gen sample = e(sample)

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col1, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col2: /// patents by male inventors
>         reghdfe ash_f1allpat_m trust_sd ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      22.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8983
                                                  Adj R-squared   =     0.8841
                                                  Within R-sq.    =     0.0024
Number of clusters (mainethcode) =         38     Root MSE        =     0.5182

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1al~t_m | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |    .061379   .0152235     4.03   0.000     .0305332    .0922248
     firmage |   -.004919   .0063664    -0.77   0.445    -.0178186    .0079806
    firmage2 |   .0000974   .0000494     1.97   0.056    -2.70e-06    .0001975
      gender |  -.0136408    .027989    -0.49   0.629     -.070352    .0430703
         age |  -.0033358   .0105593    -0.32   0.754     -.024731    .0180594
        age2 |   .0000158   .0000877     0.18   0.858    -.0001618    .0001934
      yrinco |   .0039445   .0004964     7.95   0.000     .0029387    .0049504
             |
   education |
          2  |   .0695373   .0402547     1.73   0.092    -.0120264     .151101
          3  |   .0780523   .0279093     2.80   0.008     .0215027    .1346018
          4  |   .1131122   .0314198     3.60   0.001     .0494496    .1767748
             |
       _cons |   .6536415   .3046419     2.15   0.039     .0363783    1.270905
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col2, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col3: /// patents by female inventors, by CEO's gender norms
>         reghdfe ash_f1allpat_f c.trust_sd##c.LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      18.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8922
                                                  Adj R-squared   =     0.8770
                                                  Within R-sq.    =     0.0019
Number of clusters (mainethcode) =         38     Root MSE        =     0.3140

                                     (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------------
                       |               Robust
        ash_f1allpat_f | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              trust_sd |     .01874   .0071743     2.61   0.013     .0042035    .0332765
             LFPR_sd_c |   .0279121   .0579765     0.48   0.633    -.0895595    .1453836
                       |
c.trust_sd#c.LFPR_sd_c |   -.004817   .0107942    -0.45   0.658    -.0266882    .0170542
                       |
               firmage |   -.010251   .0049991    -2.05   0.047    -.0203802   -.0001218
              firmage2 |   .0000391   .0000339     1.16   0.255    -.0000295    .0001078
                gender |   -.007332   .0208651    -0.35   0.727    -.0496086    .0349447
                   age |   .0010118   .0028281     0.36   0.723    -.0047186    .0067421
                  age2 |  -.0000257    .000024    -1.07   0.290    -.0000743    .0000228
                yrinco |   .0027097   .0004839     5.60   0.000     .0017291    .0036902
                       |
             education |
                    2  |   .0060795   .0166145     0.37   0.717    -.0275847    .0397437
                    3  |   .0204081    .016581     1.23   0.226    -.0131883    .0540045
                    4  |   .0211841   .0152565     1.39   0.173    -.0097286    .0520968
                       |
                 _cons |   .4054053   .1485088     2.73   0.010      .104498    .7063126
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col3, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col4: /// patents by male inventors, by CEO's gender norms
>         reghdfe ash_f1allpat_m c.trust_sd##c.LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin                       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      21.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8983
                                                  Adj R-squared   =     0.8841
                                                  Within R-sq.    =     0.0024
Number of clusters (mainethcode) =         38     Root MSE        =     0.5182

                                     (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------------
                       |               Robust
        ash_f1allpat_m | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              trust_sd |    .058758   .0141536     4.15   0.000     .0300801    .0874358
             LFPR_sd_c |   .1485104   .1246289     1.19   0.241    -.1040117    .4010326
                       |
c.trust_sd#c.LFPR_sd_c |  -.0308365   .0273725    -1.13   0.267    -.0862984    .0246254
                       |
               firmage |  -.0049842   .0064196    -0.78   0.442    -.0179915    .0080231
              firmage2 |   .0000978   .0000496     1.97   0.056    -2.68e-06    .0001982
                gender |  -.0142808   .0284578    -0.50   0.619    -.0719416    .0433801
                   age |  -.0032727   .0105956    -0.31   0.759    -.0247415     .018196
                  age2 |   .0000149   .0000879     0.17   0.866    -.0001633     .000193
                yrinco |   .0039314   .0005057     7.77   0.000     .0029068    .0049561
                       |
             education |
                    2  |    .068515   .0403277     1.70   0.098    -.0131967    .1502267
                    3  |   .0770788   .0278957     2.76   0.009     .0205566    .1336009
                    4  |   .1122895   .0314626     3.57   0.001     .0485403    .1760387
                       |
                 _cons |   .6694748   .3063109     2.19   0.035     .0488299     1.29012
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "None"

added macro:
         e(qualweight) : "None"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col4, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col5: /// citation-weighted patents by female inventors
>         reghdfe ash_f1allpat_citff_f trust_sd ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =       6.80
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8197
                                                  Adj R-squared   =     0.7944
                                                  Within R-sq.    =     0.0018
Number of clusters (mainethcode) =         38     Root MSE        =     0.7366

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1al~f_f | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |   .0748378   .0235405     3.18   0.003     .0271403    .1225353
     firmage |  -.0251828   .0104374    -2.41   0.021    -.0463311   -.0040346
    firmage2 |  -.0000571   .0000613    -0.93   0.357    -.0001813     .000067
      gender |   .0460686   .0244131     1.89   0.067     -.003397    .0955341
         age |  -.0223498   .0109009    -2.05   0.047    -.0444371   -.0002625
        age2 |   .0001881   .0000948     1.98   0.055    -4.07e-06    .0003802
      yrinco |   .0038041   .0016011     2.38   0.023       .00056    .0070482
             |
   education |
          2  |  -.0059921   .0696885    -0.09   0.932    -.1471944    .1352103
          3  |   .0195876    .047842     0.41   0.685    -.0773495    .1165248
          4  |   .0487222   .0622613     0.78   0.439    -.0774312    .1748756
             |
       _cons |   1.427947   .2232963     6.39   0.000     .9755057    1.880388
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col5, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col6: /// citation-weighted patents by male inventors
>         reghdfe ash_f1allpat_citff_m trust_sd ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  10,     37) =      14.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8312
                                                  Adj R-squared   =     0.8075
                                                  Within R-sq.    =     0.0015
Number of clusters (mainethcode) =         38     Root MSE        =     1.0824

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1al~f_m | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    trust_sd |    .093674   .0255296     3.67   0.001     .0419461    .1454018
     firmage |  -.0236668   .0123405    -1.92   0.063     -.048671    .0013374
    firmage2 |   .0001554   .0000863     1.80   0.080    -.0000195    .0003303
      gender |    .037737   .0660535     0.57   0.571    -.0961001     .171574
         age |  -.0209808   .0213287    -0.98   0.332    -.0641969    .0222353
        age2 |   .0001876   .0001828     1.03   0.311    -.0001827    .0005579
      yrinco |   .0056642   .0013835     4.09   0.000     .0028609    .0084675
             |
   education |
          2  |   .0565111   .1273316     0.44   0.660    -.2014873    .3145095
          3  |   .0604962   .1060828     0.57   0.572    -.1544479    .2754404
          4  |    .120319   .1195146     1.01   0.321    -.1218405    .3624786
             |
       _cons |   1.893855   .5970045     3.17   0.003      .684209    3.103501
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col6, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col7: /// citation-weighted patents by female inventors, by CEO's gender norms
>         reghdfe ash_f1allpat_citff_f c.trust_sd##c.LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =       6.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8197
                                                  Adj R-squared   =     0.7944
                                                  Within R-sq.    =     0.0021
Number of clusters (mainethcode) =         38     Root MSE        =     0.7365

                                     (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------------
                       |               Robust
  ash_f1allpat_citff_f | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              trust_sd |   .0580488   .0181276     3.20   0.003     .0213188    .0947789
             LFPR_sd_c |   .3131672    .183457     1.71   0.096    -.0585519    .6848864
                       |
c.trust_sd#c.LFPR_sd_c |  -.0511179   .0361717    -1.41   0.166    -.1244088     .022173
                       |
               firmage |  -.0248055   .0106947    -2.32   0.026     -.046475   -.0031361
              firmage2 |  -.0000585   .0000604    -0.97   0.339    -.0001809    .0000639
                gender |   .0420716   .0237388     1.77   0.085    -.0060278     .090171
                   age |  -.0223958   .0111766    -2.00   0.052    -.0450418    .0002501
                  age2 |   .0001869   .0000971     1.92   0.062    -9.88e-06    .0003836
                yrinco |   .0038633   .0016284     2.37   0.023     .0005639    .0071628
                       |
             education |
                    2  |  -.0112878   .0707386    -0.16   0.874    -.1546177    .1320422
                    3  |   .0132508   .0488709     0.27   0.788    -.0857711    .1122727
                    4  |   .0465392   .0627393     0.74   0.463    -.0805826     .173661
                       |
                 _cons |   1.525027    .217254     7.02   0.000     1.084828    1.965225
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col7, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. eststo col8: /// citation-weighted patents by male inventors, by CEO's gender norms
>         reghdfe ash_f1allpat_citff_m c.trust_sd##c.LFPR_sd_c ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin                       
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      14.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8312
                                                  Adj R-squared   =     0.8075
                                                  Within R-sq.    =     0.0017
Number of clusters (mainethcode) =         38     Root MSE        =     1.0824

                                     (Std. err. adjusted for 38 clusters in mainethcode)
----------------------------------------------------------------------------------------
                       |               Robust
  ash_f1allpat_citff_m | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------------+----------------------------------------------------------------
              trust_sd |   .0749881   .0231388     3.24   0.003     .0281044    .1218717
             LFPR_sd_c |   .3206399   .2420382     1.32   0.193     -.169776    .8110558
                       |
c.trust_sd#c.LFPR_sd_c |  -.0504898    .049157    -1.03   0.311    -.1500914    .0491118
                       |
               firmage |  -.0232121   .0121854    -1.90   0.065    -.0479021    .0014778
              firmage2 |   .0001537   .0000856     1.80   0.081    -.0000197     .000327
                gender |   .0332929   .0660955     0.50   0.617    -.1006293    .1672151
                   age |  -.0210516   .0215982    -0.97   0.336    -.0648137    .0227104
                  age2 |   .0001865   .0001854     1.01   0.321    -.0001892    .0005622
                yrinco |   .0057364   .0013708     4.18   0.000      .002959    .0085138
                       |
             education |
                    2  |   .0506719   .1266353     0.40   0.691    -.2059155    .3072593
                    3  |    .053439   .1052439     0.51   0.615    -.1598054    .2666834
                    4  |   .1180244   .1194041     0.99   0.329    -.1239112    .3599601
                       |
                 _cons |   2.001713   .5806558     3.45   0.001     .8251929    3.178234
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local qualweight "Fwd cites"

added macro:
         e(qualweight) : "Fwd cites"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col8, addscalars(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. 
. global coeflist = "trust_sd LFPR_sd_c c.trust_sd#c.LFPR_sd_c"

. esttab /*using "Table A13_Effect by gender and gender norms_Panel B.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         nomtitle collabels(none) label varwidth(28) modelwidth(12) ///
>         mgroups("arsinh(Future patent applications)", pattern(1 0 0 0 0 0 0 0) ///
>                 prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(${coeflist}) order(${coeflist}) ///
>         coeflab(trust_sd "CEO's trust" ///
>                         LFPR_sd_c "F/M LFP ratio (z-score)" ///
>                         c.trust_sd#c.LFPR_sd_c "Trust $\times$ F/M LFP ratio") ///
>         stats(qualweight FE controls N nofirms, fmt(%9.0fc %9.0fc) ///
>                 lab("Quality weight" "Firm \& Year FEs" "Baseline controls" "Observations" "Firms"))

------------------------------------------------------------------------------------------------------------------------------------------------------------
                             \multicolumn{8}{c}{arsinh(Future patent applications)}                                                                         
                                      (1)             (2)             (3)             (4)             (5)             (6)             (7)             (8)   
------------------------------------------------------------------------------------------------------------------------------------------------------------
CEO's trust                         0.020***        0.061***        0.019**         0.059***        0.075***        0.094***        0.058***        0.075***
                                  (0.007)         (0.015)         (0.007)         (0.014)         (0.024)         (0.026)         (0.018)         (0.023)   
F/M LFP ratio (z-score)                                             0.028           0.149                                           0.313*          0.321   
                                                                  (0.058)         (0.125)                                         (0.183)         (0.242)   
Trust $\times$ F/M LFP ratio                                       -0.005          -0.031                                          -0.051          -0.050   
                                                                  (0.011)         (0.027)                                         (0.036)         (0.049)   
------------------------------------------------------------------------------------------------------------------------------------------------------------
Quality weight                       None            None            None            None       Fwd cites       Fwd cites       Fwd cites       Fwd cites   
Firm \& Year FEs                        X               X               X               X               X               X               X               X   
Baseline controls                       X               X               X               X               X               X               X               X   
Observations                       29,384          29,384          29,384          29,384          29,384          29,384          29,384          29,384   
Firms                               3,598           3,598           3,598           3,598           3,598           3,598           3,598           3,598   
------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. 
. //PRINT DIFFERENCES
. quietly {
WARNING: Singleton observations not dropped; statistical significance is biased (link)

. 
. quietly {

. test [Female_mean]m_trust_sd = [Male_mean]m_trust_sd

 ( 1)  [Female_mean]m_trust_sd - [Male_mean]m_trust_sd = 0

           chi2(  1) =   13.30
         Prob > chi2 =    0.0003

. 
. quietly {

. test [Female_mean]m_trust_sd = [Male_mean]m_trust_sd

 ( 1)  [Female_mean]m_trust_sd - [Male_mean]m_trust_sd = 0

           chi2(  1) =    1.81
         Prob > chi2 =    0.1779

. 
. cap log close
